@article{UlmerBraunChengetal.2023,
  author    = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg},
  title     = {A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation},
  series = {International Journal of Production Research},
  journal   = {International Journal of Production Research},
  publisher = {Taylor \& Francis},
  issn      = {0020-7543 (Print)},
  doi       = {10.1080/00207543.2023.2166140},
  year      = {2023},
  abstract  = {Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers' cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.},
  language  = {en}
}
@article{SchifferFerrein2016,
  author    = {Schiffer, Stefan and Ferrein, Alexander},
  title     = {Decision-Theoretic Planning with Fuzzy Notions in GOLOG},
  series = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
  volume    = {24},
  journal   = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
  number    = {Issue Suppl. 2},
  publisher = {World Scientific},
  address   = {Singapur},
  issn      = {1793-6411},
  doi       = {10.1142/S0218488516400134},
  pages     = {123 -- 143},
  year      = {2016},
  abstract  = {In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog's forward-search DT planning algorithm, these formulas are evaluated in order to find the agent's optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.},
  language  = {en}
}
@article{FerreinSteinbauer2016,
  author    = {Ferrein, Alexander and Steinbauer, Gerald},
  title     = {The Interplay of Aldebaran and RoboCup},
  series = {KI - K{\"u}nstliche Intelligenz},
  volume    = {30},
  journal   = {KI - K{\"u}nstliche Intelligenz},
  number    = {3-4},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1610-1987},
  doi       = {10.1007/s13218-016-0440-1},
  pages     = {325 -- 326},
  year      = {2016},
  language  = {en}
}
@article{NiemuellerKarrasFerrein2017,
  author    = {Niemueller, Tim and Karras, Ulrich and Ferrein, Alexander},
  title     = {Meisterschaft der Maschinen: Die Industrial Logistic Liga},
  series = {C´t Magazin f{\"u}r Computertechnik},
  journal   = {C´t Magazin f{\"u}r Computertechnik},
  number    = {26},
  year      = {2017},
  language  = {de}
}
@article{SchulteTiggesFoersterNikolovskietal.2022,
  author    = {Schulte-Tigges, Joschua and F{\"o}rster, Marco and Nikolovski, Gjorgji and Reke, Michael and Ferrein, Alexander and Kaszner, Daniel and Matheis, Dominik and Walter, Thomas},
  title     = {Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments},
  series = {Sensors},
  volume    = {22},
  journal   = {Sensors},
  number    = {19},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s22197146},
  pages     = {20 Seiten},
  year      = {2022},
  abstract  = {Abstract In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.},
  language  = {en}
}
@article{ClaerFerreinSchiffer2019,
  author    = {Claer, Mario and Ferrein, Alexander and Schiffer, Stefan},
  title     = {Calibration of a Rotating or Revolving Platform with a LiDAR Sensor},
  series = {Applied Sciences},
  volume    = {Volume 9},
  journal   = {Applied Sciences},
  number    = {issue 11, 2238},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2076-3417},
  doi       = {10.3390/app9112238},
  pages     = {18 Seiten},
  year      = {2019},
  language  = {en}
}
@article{SteinbauerFerrein2016,
  author    = {Steinbauer, Gerald and Ferrein, Alexander},
  title     = {20 Years of RoboCup},
  series = {KI - K{\"u}nstliche Intelligenz},
  volume    = {30},
  journal   = {KI - K{\"u}nstliche Intelligenz},
  number    = {3-4},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1610-1987},
  doi       = {10.1007/s13218-016-0442-z},
  pages     = {221 -- 224},
  year      = {2016},
  language  = {en}
}